期刊
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
卷 52, 期 8, 页码 2211-2231出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/00207543.2013.848492
关键词
estimation of distribution algorithm; multi-objective optimisation; restarting strategy; heuristic rule; NSGA-II; lot-streaming flow shop
资金
- Natural Science Foundation of China [61105063, 61075061, 61104179, 61174187]
- Fundamental Research Funds for the Central Universities and Research, Innovation Project for College Graduates of Jiangsu Province [CXZZ13 0932]
- Basic scientific research foundation of Northeast University [N110208001]
- starting foundation of Northeast University [29321006]
- Science Foundation of Liaoning Province in China [2013020016]
Crossover and mutation operators in NSGA-II are random and aimless, and encounter difficulties in generating offspring with high quality. Aiming to overcoming these drawbacks, we proposed an improved NSGA-II algorithm (INSGA-II) and applied it to solve the lot-streaming flow shop scheduling problem with four criteria. We first presented four variants of NEH heuristic to generate the initial population, and then incorporated the estimation of distribution algorithm and a mutation operator based on insertion and swap into NSGA-II to replace traditional crossover and mutation operators. Last but not least, we performed a simple and efficient restarting strategy on the population when the diversity of the population is smaller than a given threshold. We conducted a serial of experiments, and the experimental results demonstrate that the proposed algorithm outperforms the comparative algorithms.
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